collaborators

8 papers

cs.CL2026

LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs

Pei-Fu Guo, Yun-Da Tsai, Chun-Chia Hsu +6

Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either from genuine transfer or from prior ex…

cs.CL2026

DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning

Yicheng Chen, Zerun Ma, Xinchen Xie +2

In the current landscape of Large Language Models (LLMs), the curation of large-scale, high-quality training data is a primary driver of model performance. A key lever is the \emph…

cs.AI2026

Diagnosing Knowledge Conflict in Multimodal Long-Chain Reasoning

Jing Tang, Kun Wang, Haolang Lu +7

Multimodal large language models (MLLMs) in long chain-of-thought reasoning often fail when different knowledge sources provide conflicting signals. We formalize these failures und…

cs.LG2026

A-LLM: An End-to-end Conversational Audio Avatar Large Language Model

Xiaolin Hu, Hang Yuan, Xinzhu Sang +4

Developing expressive and responsive conversational digital humans is a cornerstone of next-generation human-computer interaction. While large language models (LLMs) have significa…

cs.CL2026

AEQ-Bench: Measuring Empathy of Omni-Modal Large Models

Xuan Luo, Lewei Yao, Libo Zhao +6

While the automatic evaluation of omni-modal large models (OLMs) is essential, assessing empathy remains a significant challenge due to its inherent affectivity. To investigate thi…

cs.AI2026

PsychEval: A Multi-Session and Multi-Therapy Benchmark for High-Realism AI Psychological Counselor

Qianjun Pan, Junyi Wang, Jie Zhou +10

To develop a reliable AI for psychological assessment, we introduce \texttt{PsychEval}, a multi-session, multi-therapy, and highly realistic benchmark designed to address three key…